Interdisciplinary Journal

Current Applied Sciences (Abbreviation: Curr. Appl. Sci.) is an open access, international, semiannual and peer-reviewed journal that established by the University of Zabol, Iran. The journal aims to provide a platform for academicians, researchers and scientists to share knowledge and ideas in the form of high-quality articles, original research or review covering in the following fields:

Mathematics

Physics

Chemistry

Biology

Material Science

Nanotechnology

Statistics

Biotechnology

Food Science

Computer Science

Information Technology 

All manuscripts submitted to Curr. Appl. Sci. are published Free of Charge. 

A note on the Independence Number of a Power Graph of a Cyclic Group

A note on the Independence Number of a Power Graph of a Cyclic Group

Pages 57-60

https://doi.org/10.22034/cas.2024.482591.1043

Alireza Doostabadi

Abstract Let G be a finite group. The power graph of the group G, with notation P (G) is a graph such that it’s vertex set is the group G and two distinct elements x, y are adjacent if and only if x = yn or y = xn for some positive integer . In this note, we compute bounds of independence number of power graph of a cyclic group.

Optimization of the State of an Inverted Pendulum System Using Kalman Filter in the Presence of Gaussian and Poisson Noise

Optimization of the State of an Inverted Pendulum System Using Kalman Filter in the Presence of Gaussian and Poisson Noise

Pages 61-72

https://doi.org/10.22034/cas.2025.496057.1045

Mohammadreza Pourmir

Abstract The inverted pendulum problem is an interesting equilibrium problem because the uncontrolled system is unstable and if the base does not move to maintain the vertical position, the pendulum will simply fall and its dynamics are also nonlinear. The Kalman filter is a set of mathematical equations that provides an efficient computational (recursive) solution of the least squares' method. The Kalman filter supports the estimation of past, present, and even future states, and can perform the estimation well even when the exact nature of the modeled system is unknown. This paper aims to estimate the state of the system to optimize the state created by the base in the inverted pendulum problem model so that the pendulum remains in the upright state. The generated random noise signals are added to the real measurement data generated using the system dynamics and these data are used to estimate the system states using the Kalman filter and the extended Kalman filter. The results of these estimates are analyzed and compared.

On Some Results of Geometric Mixture Models

On Some Results of Geometric Mixture Models

Pages 73-82

https://doi.org/10.22034/cas.2025.499008.1046

Omid Shojaee

Abstract Over recent decades, numerous methodologies have been developed to address the heterogeneity within populations. These methodologies vary in their application to both parametric and semi-parametric models, which are crucial for a broad spectrum of uses in reliability and survival analysis. Research indicates that mixture distributions serve as an effective approach to representing population heterogeneity. This study delves into geometric mixture models for survival functions (or distribution functions), exploring their inherent properties and features. We discuss various stochastic and distributional aspects of these mixtures. Additionally, we establish some conditions for stochastic comparisons based on the usual stochastic order, hazard rate order, and reversed hazard rate order. Furthermore, we integrate our findings with prominent semi-parametric models in reliability theory, including the additive hazard rate model, the proportional hazard rate model, the accelerated lifetime model, and the proportional reversed hazard rate model, which serve as foundational models in our geometric mixtures. To corroborate our findings, we will demonstrate numerical examples.

Investigation of Some Fuzzy Optimization Problems with Fuzzy Genetic Algorithms

Investigation of Some Fuzzy Optimization Problems with Fuzzy Genetic Algorithms

Pages 83-88

https://doi.org/10.22034/cas.2025.493776.1044

Abbas Akrami

Abstract Fuzzy optimization techniques have proven to be highly effective in the field of optimization, particularly in scenarios where decision-making processes are complex and influenced by uncertainty. These methods address vagueness and ambiguity by leveraging the principles of fuzzy logic, making them applicable across various domains such as economics, engineering, healthcare, and environmental management. Optimization techniques are essential for enhancing performance and efficiency in numerous industries. Among these, fuzzy logic provides a robust framework for handling uncertainties and imprecision commonly encountered in real-world problems. In this paper, we explore fuzzy genetic algorithms as a solution to certain fuzzy optimization problems. We demonstrate that this approach yields a reliable approximation of solutions for such problems. Additionally, we illustrate the application of this algorithm in three key areas: maximum fuzzy flow, fuzzy regression, and fuzzy controller design. The foundation of fuzzy genetic algorithms lies in the discretization of interval-based fuzzy subsets. These algorithms offer an innovative way to generate approximate solutions for fuzzy optimization problems where variables are arbitrary fuzzy subsets of specific intervals. This makes them versatile and applicable to a wide range of challenges.

A Novel Downlink Handover-Based Priority Scheduling for Providing Seamless Mobility and QoS in IEEE 802.16 BWA System

A Novel Downlink Handover-Based Priority Scheduling for Providing Seamless Mobility and QoS in IEEE 802.16 BWA System

Pages 89-108

https://doi.org/10.22034/cas.2025.220709

Hamed Fehri, Mostafa Monemizadeh

Abstract In IEEE 802.16 wireless metropolitan area networks, users can take their broadband connections with them as they move from one location to another with different speeds. Thus, providing seamless handovers and QoS (Quality-of-Service) is challenging, especially for mobile subscribers at vehicular speeds. On the other hand, time variability and unpredictability of the wireless channel may cause QoS degradation and handover losses for these users. This paper proposes a new downlink handover-based priority scheduling scheme for different scheduling services which is providing lossless handovers and QoS. Taking the power degradation rates into consideration that enables monitoring users' locations, speeds and accelerations, this scheme assigns higher priority to the users having higher probability performing handover in the near future. An AMC (Adaptive Modulation and Coding) scheme and a pre-selection method are also proposed for providing high system performance, i.e., higher system throughput and lower packet dropping rate. The analytical results show the efficiency of proposed scheme.

The Future Prospect of Integrating Machine Learning and Nanocarbon Materials in Cancer Treatment: A Prospective Review

The Future Prospect of Integrating Machine Learning and Nanocarbon Materials in Cancer Treatment: A Prospective Review

Pages 109-118

https://doi.org/10.22034/cas.2025.524909.1050

Luiz Fernando Romanholo Ferreira

Abstract Cancer, as one of the leading causes of global mortality, requires novel therapeutic approaches with high efficiency and low side effects. In this regard, combining artificial intelligence (AI), particularly machine learning (ML), with nanocarbon materials such as carbon nanotubes and graphene has brought new hope. Hence, this review aims to investigate the role of ML in optimizing diagnosis, predicting treatment response, and designing smart nanocarriers based on nanocarbon. Nanotechnology and AI enable targeted drug delivery, photothermal therapy, and more accurate imaging. For example, carbon nanoparticles can deliver chemotherapy drugs directly to tumors, while ML predictive models analyze medical images to accurately assess a patient’s response to treatment and recommend the best course of action. This convergence of technologies has opened up new hopes for the fight against cancer. However, there are challenges, such as the potential toxicity of nanocarbons, the need for extensive clinical data to train ML models, and integrating these technologies into therapeutic systems. In the future, the development of smarter nanocarriers, aided by machine learning and further studies on the biocompatibility of nanocarbons, could lead to more personalized and effective therapies. In conclusion, the integration of ML and nanocarbons has the potential to revolutionize oncology, but interdisciplinary research and large-scale clinical trials are necessary to achieve practical application.

Enhancing the Detail Resolution of Foggy Images Using Fuzzy Histogram Equalization with Weighted Distribution

Enhancing the Detail Resolution of Foggy Images Using Fuzzy Histogram Equalization with Weighted Distribution

Articles in Press, Accepted Manuscript, Available Online from 07 June 2025

https://doi.org/10.22034/cas.2025.520327.1048

Najme Ghanbari

Abstract Enhancing image quality is an essential step in developing computer vision since it can significantly increase the efficacy of other algorithms, such as object recognition. Image quality improvement has been done in many different sectors to recover and analyze various aspects. This study combines a weighted fuzzy histogram equalization method with other image quality improvement algorithms to rebuild images affected by inhomogeneous blur. This process begins by generating a phase dissimilarity histogram of the brightness of neighboring pixels to enhance contrast. Gamma correction is then used to boost the dark areas, and maximum saturation is used to prevent the fading effect. The proposed method was evaluated using the PSNR and SSIM indices. These indices are calculated for the results of the proposed method and compared to the previous images. The effectiveness of the proposed algorithm in reconstructing images and the degree to which the results closely resemble the original images will be determined by this comparison. This article also included a qualitative review, the results of which were discussed. Although this method generally sharpens visual details, it might not significantly increase scores in this particular scenario.

Biostimulant Effects of Silicon-Rich Horsetail Extract on Morphological and Growth Characteristics of Zataria multiflora

Biostimulant Effects of Silicon-Rich Horsetail Extract on Morphological and Growth Characteristics of Zataria multiflora

Articles in Press, Accepted Manuscript, Available Online from 08 September 2025

https://doi.org/10.22034/cas.2025.228771

Simin Tajik Esmaeili

Abstract Thyme is a unique plant with beneficial biological properties and is widely used in the healthcare and treatment sectors. This study was conducted to investigate the effect of horsetail extract on the morphological and growth characteristics of Zataria multiflora (ZM). For this purpose, foliar treatments with horsetail extract at concentrations of 0%, 0.5%, 1%, and 2% were applied to plants at the 7–9 leaf stage. The experiment followed a randomized complete block design with three replications. Evaluated traits included plant height, number of leaves per plant, number of sub-branches, leaf area index, plant fresh weight, plant dry weight, antioxidant activity, and essential oil composition. The results showed that the application of silicon-rich horsetail extract enhanced both growth and phytochemical traits. The 2% horsetail extract treatment significantly increased plant height, leaf length, leaf width, fresh weight, and dry weight. The highest antioxidant enzyme activity was observed under the 2% extract treatment. Additionally, essential oil content increased with higher extract concentrations. The main essential oil components identified were carvacrol (33.75–39.4%), thymol (12.81–14.35%), linalool (7.12–10.22%), and p-cymene (7.45–8.38%). The maximum levels of carvacrol (39.4%) and thymol (14.84%) were achieved at 1% and 2% extract concentrations, showing significant differences compared to the control group. Horsetail extract, rich in silicon, acts as a biostimulant and natural fertilizer, potentially improving the yield and essential oil production of Z. multiflora, particularly under organic cultivation systems.

Toxicity Challenges of Metal Nanoparticles in Zoonotic Disease Treatment: Strategies and Innovations

Toxicity Challenges of Metal Nanoparticles in Zoonotic Disease Treatment: Strategies and Innovations

Articles in Press, Accepted Manuscript, Available Online from 12 September 2025

https://doi.org/10.22034/cas.2025.534545.1052

Athena Maleki, Davood Dorranipour, Mohadese Sajedi-Moghaddam, Mostafa Peyvandi, Sérgio Amorim de Alencar

Abstract Metal nanoparticles (MNPs) have garnered significant attention for their potential application as a novel means of combating zoonotic diseases. MNPs are unique, not only due to their small size but also their high surface-to-volume ratio and their potent antimicrobial properties. Despite the challenges posed by parasitic zoonotic diseases that are transmitted from animals to people, their effective treatment remains a serious public health concern. Although MNPs have been shown to have some potential advantages, several challenges are associated with their use, including cytotoxicity, bioaccumulation, adverse immune reactions, and unanticipated, possibly harmful side effects that may adversely affect health. The purpose of this review article is to examine the challenges associated with the toxicity and side effects of MNPs in the treatment of parasitic zoonotic diseases, as well as potential strategies that can be adopted to minimize these impacts. Recent studies in this area have focused on optimizing nanoparticle design and surface modification, utilizing biocompatible coatings, reducing therapeutic doses, and developing targeted drug delivery systems, thereby maximizing efficiency and accelerating the delivery of drug. Several solutions have been proposed in this regard, including the surface engineering of nanoparticles with biocompatible coatings, nanoliposomes, and magnetic nanoparticles designed to deliver drugs specifically, as well as innovative technologies that can help control the release of drugs. Furthermore, it is possible to develop toxicity prediction models using artificial intelligence and bioinformatic analyses to help identify risks arising from the use of nanoparticles more accurately.

Prospects and Challenges of Nanotechnology in the Treatment of Pediatric Diseases

Prospects and Challenges of Nanotechnology in the Treatment of Pediatric Diseases

Articles in Press, Accepted Manuscript, Available Online from 07 September 2025

https://doi.org/10.22034/cas.2025.536702.1053

Kiarash Abdollahi, Noushin Moradi, Melina Barahouei Moghaddam, Samira Lashani, Mohammad Sajjad Najimi, Fatemeh Ghorbannejad Nashli, Yeganeh Yazdanshenas, Mahsa Mohammadian

Abstract As a new approach, nanotechnology has opened up new horizons in disease diagnosis and treatment. Nanotechnology, utilizing nanomaterials and targeted drug delivery systems, has addressed numerous challenges in treating pediatric diseases. Pediatric diseases present unique challenges in treatment management due to the specific physiological characteristics of this age group, including the need for accurate drug dosages, minimizing side effects, and enhancing treatment efficacy. Nanotechnology offers groundbreaking applications in the diagnosis and treatment of childhood diseases, providing targeted therapies with enhanced efficacy and reduced side effects. Key applications include nano-drug delivery systems for the precise treatment of pediatric cancers (e.g., leukemia and brain tumors), nanosensors for the early detection of metabolic and infectious diseases, and nanoparticle-based inhalable therapies for respiratory conditions such as asthma. Additionally, nanotechnology enables improved bioavailability and reduced drug dosages, critical for pediatric patients. However, challenges such as long-term safety, biocompatibility, and regulatory hurdles remain. Future directions include the development of multifunctional nanoplatforms for combination therapy and personalized medicine, alongside advances in scalable and cost-effective manufacturing. Addressing these challenges will be essential for translating nanomedicine into mainstream pediatric healthcare.

Investigation of the Mutual Interactions of the Sodium Ion and Some 15-Crown-5 Ethers through an Experimentally Based QSPR Model and Quantum Mechanical Features

Investigation of the Mutual Interactions of the Sodium Ion and Some 15-Crown-5 Ethers through an Experimentally Based QSPR Model and Quantum Mechanical Features

Articles in Press, Accepted Manuscript, Available Online from 02 November 2025

https://doi.org/10.22034/cas.2025.233426

Mahmood Sanchooli, Pouya Karimi, Fereshteh Shiri

Abstract The mutual interactions between the sodium ion (Na+) and hydrogen, carbon and oxygen atoms of the rings of a number of 15-crown-5 ether (15C5) derivatives were explored. Three different categories of descriptors including dipole moments, orbital energies and atomic charges were obtained from quantum mechanical calculations. A reliable correlation between stability constant (logK) of the 15C5 ethers and the mentioned electronic features was constructed. The model reveals considerable contributions of the C8 and C9 atoms in comparison to the other atoms in the rings. Moreover, quantum mechanical calculations confirmed the role of these two carbon atoms on the stability of the structures. Furthermore, a quantitative structure property relationship (QSPR) model was conducted on stability constant values of the mentioned complexes. Furthermore, it is found that a significant electron charge density has condensed between the hydrogen atoms of the rings and sodium ion. Also, ionic character of the interactions between the sodium ion and oxygen atoms of the ring was verified.

Surface Plasmon Excitation in a Spherical Nanocavity: The Hydrodynamical Drude Model

Surface Plasmon Excitation in a Spherical Nanocavity: The Hydrodynamical Drude Model

Articles in Press, Accepted Manuscript, Available Online from 24 February 2026

https://doi.org/10.22034/cas.2026.574826.1060

Moslem Mir

Abstract We theoretically study nonlocal effects in surface plasmon excitations in a spherical dielectric nanocavity embedded in a metallic host within the framework of the hydrodynamic Drude model. An analytical expression for the surface plasmon resonance frequencies is derived, enabling a transparent interpretation of size-dependent and material-dependent plasmonic behavior beyond the local approximation. Nonlocality is shown to modify the plasmonic response, leading to a blueshift of the resonance frequencies as the nanocavity radius decreases. We further demonstrate that the background dielectric constant associated with the metal ion core plays an essential role in the excitation process. For nanocavities with dielectric constants smaller than that of the metallic background, the surface plasmon resonances shift to higher frequencies, while a redshift occurs when the cavity dielectric constant exceeds the background value. In addition, increasing the nanocavity dielectric constant enhances the influence of nonlocal effects on surface plasmon excitations. These parameters offer valuable guidance for the design of subwavelength plasmonic structures.

On <em>N</em>(<em>k</em>)-quasi Einstein Manifolds Satisfying Some Conditions

On N(k)-quasi Einstein Manifolds Satisfying Some Conditions

Articles in Press, Accepted Manuscript, Available Online from 20 January 2026

https://doi.org/10.22034/cas.2026.569904.1058

Ali Akbar Hosseinzadeh

Abstract In this paper, we study -curvature tensor on -quasi Einstein manifolds. The tensor ​ is defined as a modification of the Riemannian curvature tensor involving the Ricci operator. Several of its basic properties are first derived with respect to the structure vector field , the associated 1-form , and the Riemannian metric . Using these relations, we investigate curvature conditions involving . In particular, we consider the condition  and . All the results obtained are in the form of necessary and sufficient conditions. 2010 AMS Classification: 53C25

Molecular Identification of Brucella Bacteria Using BLS and Omp31 Genes

Molecular Identification of Brucella Bacteria Using BLS and Omp31 Genes

Volume 3, Issue 1, February 2025, Pages 11-20

https://doi.org/10.22034/cas.2023.391375.1031

Masoumeh Noura, Hossein Kamaladini, Fatemeh Haddadi, Mohsen Najimi

Abstract Brucellosis or Malta fever (Mediterranean fever) is an important zoonosis caused by different species of Brucella – a small, Gram-negative, aerobic, non-motile, non-encapsulated, and non-spore-forming coccobacillus. Brucellosis can be easily transmitted to humans by Brucella-contaminated blood, meat, or milk. The lack of an effective tool for vaccination or efficient treatment has necessitated rapid bacterial detection methods for preventing this disease. In this study, we optimized the molecular detection of Brucella through polymerase chain reaction (PCR) and multiplex-PCR. To this end, the Omp31 and BLS genes were amplified, resulting in two fragments of 347 bp and 256 bp, respectively. PCR and multiplex-PCR specificity and sensitivity for genomic DNA were 100% and 0.39 ng/μL, respectively. The detection time of Brucella was less than 2 hours, which is obviously shorter than the identification time of the traditional methods like culture, which usually takes more than a day. Given the high specificity and sensitivity of Brucella detection with these genes through multiplex-PCR, we suggest this approach for evaluating the contamination of livestock in veterinary reference laboratories.

Comparison and Optimization of RNA Extraction from Formalin-Fixed Paraffin-Embedded Tissues of Hepatocellular Carcinoma

Comparison and Optimization of RNA Extraction from Formalin-Fixed Paraffin-Embedded Tissues of Hepatocellular Carcinoma

Volume 1, Issue 1, June 2023, Pages 9-20

https://doi.org/10.22034/cas.2021.144303

Nasim Hafezi, Seyedeh Maryam Hosseini-khah, Zahra Hosseini-khah, Alireza Rafiei

Abstract Detection of a new molecular marker for diagnosis and treatment of cancer is a growing field of recent research. The main challenge for molecular investigation is nucleic acid extraction from formalin-fixed, paraffin-embedded tissue (FFPE) of fine-needle aspiration (FNA) samples. In this research, we have compared four different commercially available RNA isolation kits by evaluating the quality and quantity of total RNA. RNA extraction of 10 FNA-FFPE of hepatocellular carcinoma and 10 normal tissue samples were compared and optimized using four commercially available kits: Isol-RNA lysis Reagent (5-PRIME), Cinna Pure RNA kit (SinaClon BioScience), Denazist RNA extraction kit (DENAzist Asia Biotechnology), and RNeasy FFPE Kit (Qiagen) to use in downstream applications. Evaluation of RNA extracting was done by spectrophotometer and electrophoresis. Also, quantitative reverse-transcription PCR was used for assessing the expression of SOX2. RNeasy FFPE Kit had the highest concentration of RNA between the four commercial kits (106.2 ± 17.15) and also, the highest RNA integrity with some modification. The most preferred kit for RNA extraction based on gene amplification was the RNeasy FFPE Kit, which has the lowest CT due to the high quality and integrity of RNA compared to the other three kits with the same modification. Our results suggested that RNeasy FFPE Kit with some modifications in temperature and incubation time was the best kit for RNA extraction from FNA-FFPE issues to a considerable extent with high purity and maintaining the integrity of RNA.

Laboratory-Based Diagnostic Tools for COVID-19: An Overview of Challenges and Limitations

Laboratory-Based Diagnostic Tools for COVID-19: An Overview of Challenges and Limitations

Volume 2, Issue 1, June 2024, Pages 13-30

https://doi.org/10.22034/cas.2022.340428.1018

Surabhi Shukla, Suruchi Singh, Namrata Khanna, Tanushri Chatterji, Upasana Yadav, Reeta Maurya, Sadanand Pandey

Abstract The spread of severe acute respiratory syndrome coronavirus-2 (SARS Cov-2) as a pandemic has been a catastrophic clinical situation afflicting millions and affecting the socioeconomic scenario across the world. These unprecedented circumstances have evoked the need for an early and accurate diagnosis, followed by immediate and effective treatment of the disease. A reliable, rapid, and correct diagnosis is required to prevent transmission and for early patient management. False-negative results hasten the spread of the contagion, while false-positive results cause nonessential therapy and may result in unwarranted agony to the individual. Therefore, detection of the virus should be through accurate, rapid, and convenient diagnostic tests. Various immunological and nucleic acid amplification-testing kits are currently in use. Reverse transcription-polymerase chain reaction (RT-PCR) is a promising technique for COVID-19 diagnosis, but it is not accessible at the primary hospital level. For accurate detection of the coronavirus, sample collection plays a crucial role. Usually, a nasopharyngeal swab is collected as a sample. However, in some instances, to confirm detection, sputum and bronchoalveolar lavage (BAL) samples may be obtained from the lower part of the respiratory tract. The purpose of this review is to provide a brief overview of the specimen selection and laboratory techniques available for detecting SARS Cov-2 so that medical professionals can strategize the setting up of sophisticated and well-equipped diagnostic centers.

Elastic Constants and Elastic Moduli of Silicon Carbide Nanosheet

Elastic Constants and Elastic Moduli of Silicon Carbide Nanosheet

Volume 1, Issue 2, December 2023, Pages 59-64

https://doi.org/10.22034/cas.2022.144399

Samira Salimi, Hojat Allah Badehian, Ziad Badehian

Abstract 2-Dmensional silicon carbide (2D SiC) provides several advantages compared to the bulk silicon carbide, due to its two-dimensional structure. Elastic constants and elastic moduli of 2D carbide nanotubes were calculated employing density functional theory (DFT). There are six independent elastic constants for tetragonal lattice with (422, 4mm, -42/m, 4/mmm) point group. The calculated , , , , ,  of 2D SiC are reported in this work. The results suggest that the shear modulus of 2D SiC is 27.78 GPa, which is lower than that of the of single layered graphene sheet (=0.22 TPa). The bulk modulus of 2D SiC is 44.98 GPa as well. Moreover, Young’s modulus of 2D SiC is lower than Young’s modulus of single layered graphene sheet. Compared to Young’s modulus of the amorphous phase of the SiC (=313.6 GPa), Young’s modulus of 2D SiC (=156.19 GPa) is smaller. The main reason is that the stiffness of the 2D SiC in the x direction is smaller than the stiffness of the bulk SiC.

Determination of Phenolic and Flavonoid Contents of Roots and Shoots of Euphorbia serpens Kunth Using Different Solvents

Determination of Phenolic and Flavonoid Contents of Roots and Shoots of Euphorbia serpens Kunth Using Different Solvents

Volume 2, Issue 1, June 2024, Pages 59-66

https://doi.org/10.22034/cas.2022.354096.1026

Mehdi Dehghani, Hamid Beyzaei, Zahra Ebrahimnezhad

Abstract Euphorbia serpens Kunth (Euphorbiaceae) is an exotic annual plant species native to South America but is regarded as a pantropical weed. In this paper, the total phenolic and flavonoid contents of ethanolic, methanolic, dichloromethane, and petroleum ether extracts of shoots and roots of Euphorbia serpens were assessed in vitro. The plant materials were collected from Zabol, Sistan and Baluchestan in June 2022. The Folin-Ciocalteu and aluminum chloride colorimetric instructions were followed to evaluate the total phenolic and flavonoid contents of the extracts, respectively. The methanolic extract of aerial parts contained the highest amount of phenolic compounds (59.205 mg GAE/g), while the lowest content of phenols was found in the dichloromethane extract of roots (29.794 mg GAE/g). Also, the greatest amount of flavonoids was recorded for methanol extracts of aerial parts (34 mg RE/g), whereas the ethanol extract of roots contained the lowest amount of flavonoids (1.204 mg q/g). The aerial parts of Euphorbia serpens, in general, contain higher amounts of polyphenols as compared with the underground parts. The results also showed that phenolic and flavonoid contents vary significantly with the employed solvent. It can be concluded that the aerial parts of Euphorbia serpens are rich sources of polyphenolic compounds, signaling their potential for high antioxidant activity and nutritional and pharmaceutical importance.

Application of Space-Charge Model in Describing the Ionic Conductivity of Lithium-Borate Thin Films

Application of Space-Charge Model in Describing the Ionic Conductivity of Lithium-Borate Thin Films

Volume 3, Issue 1, February 2025, Pages 1-10

https://doi.org/10.22034/cas.2023.388234.1030

Mohammad Reza Shoar Abouzari

Abstract Ionic conduction of lithium-borate thin films shows a nontrivial increase when the layer thickness is less than 120 nanometers. In this research, the space-charge model is used to describe high conductivity in lithium-borate thin films. Regarding the amorphous structure of these layers, similar to the crystalline structure, we assume the Li+ ions and their counterparts as defects and the regions adjacent to electrode-electrolyte interfaces as space-charge regions. The electrochemical potential of defects arising from these regions leads to the well-known Poisson-Boltzmann equation. To solve this equation numerically, the fourth-order Rung-Kutta integration, together with a shooting method for two-point boundary value problems, is used. Since these two boundary conditions are at two different points, the shooting method is used to solve this problem. Finally, the calculated ionic conductivity is compared to the experimental one. A free parameter that is related to the size of the space-charge region is used to fit space-charge model data to the experimental results. Although the space charge model is used in this research to describe the ionic conductivity of lithium borate, it is expected that this model can be used for other ionic conductors by changing the model parameters.

Nonenzymatic Electrochemical Detection of Glucose Using Screen-Printed Electrode Modified with Pd‒Au Nanoparticles Encapsulated on Dendrimer Grafted Multi-Wall Carbon Nanotubes

Nonenzymatic Electrochemical Detection of Glucose Using Screen-Printed Electrode Modified with Pd‒Au Nanoparticles Encapsulated on Dendrimer Grafted Multi-Wall Carbon Nanotubes

Volume 2, Issue 2, December 2024, Pages 67-78

https://doi.org/10.22034/cas.2022.343533.1019

Hamid Ahmar

Abstract A novel nonenzymatic glucose sensor based on palladium‒gold nanoparticles encapsulated on polypropylene amine dendrimer–grafted multi-wall carbon nanotubes (PdAu/PPI‒MWCNTs) has been successfully fabricated and applied to glucose detection. PdAu/PPI‒MWCNTs was prepared in a three‒step process. First, polypropylene amine (PPI) dendrimers were grown on the surface of functionalized multi-wall carbon nanotubes (MWCNTs‒NH2) by a divergent method; second, metal ions were trapped within the dendrimers; and third, the ions were chemically reduced. Therefore, the well-distributed nanoparticles with an average size range of 1.6-3.2 nm were obtained on the surface of PPI‒MWCNTs. The prepared PdAu/PPI‒MWCNTs nanocomposite was immobilized on screen-printed carbon electrode and its electrocatalytic activity for glucose oxidation reaction was studied. Under the optimized conditions, the glucose oxidation current was linear to its concentration within the range of 0.03 ‒ 3.0 mM, and the detection limit was found to be 0.01 mM (S/N = 3). Finally, the prepared sensor has been successfully applied to determine the glucose content in human blood serum samples.